Développeur IA Générative Confirmé (H/F) – RAG, Agents IA & Industrialisation LLMOps
Tasks
- Add guardrails
- Analyze errors and hallucinations
- Apply LLMOps best practices
- Build AI agents
- Build OCR pipelines
- Build conversational assistants
- Chunk documents
- Collaborate with business teams on requirements
- Contribute to technical feasibility studies
- Deploy with Docker
- Deploy with Kubernetes
- Design RAG pipelines
- Develop AI APIs and microservices
- Evaluate model outputs
- Extract information from documents
- Generate embeddings
- Generate summaries and corpus analysis
- Implement AI observability
- Implement document search
- Improve continuously
- Index and update corpora
- Industrialize solutions with testing
- Ingest documents
- Integrate LLMs in applications
- Log and trace executions
- Manage model lifecycles
- Monitor prompts and response quality
- Orchestrate multi step tasks
- Provision with Terraform
- Set up CI/CD
- Track latency and costs
- Transform documents
- Version prompts
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | AI Search | AWS | Asyncio | Azure | Azure AI | Azure AI Search | CrewAI | Data extraction | Datadog | Docker | Elasticsearch | Embeddings | FastAPI | GCP | GitHub Actions | GitLab CI | Grafana | Hybrid search | Integration Testing | Jenkins | Kubernetes | LLM Evaluation | LLM integration | Langchain | Langfuse | Langgraph | Llamaindex | Microservices | Milvus | OCR | Observability | Orchestration | Pinecone | PostgreSQL | Prometheus | Prompt engineering | Pydantic | Python | Qdrant | RAG | REST API | RGPD | Semantic Kernel | Terraform | Unit Testing | Vector Search | Weaviate
Education
Roles
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